DURAARK ENRICHING BIM AND POINT CLOUD DATA FOR THE … Tamke.pdf · 1 05 / 28 / 15 Martin Tamke...

1 05 / 28 / 15 Martin Tamke (CITA) / Copenhagen

CITA - Centre for Information Technology and Architecture // Copenhagen

DURAARK – ENRICHING BIM AND POINT CLOUD

DATA FOR THE USE IN BUILDING LIFECYCLES 28. MAY 2015 – LISBON– GEOSPATIAL WORLD FORUM - GEOBIM


CITA: Bridging Digital Design and its materialisation

http://cita.karch.dk


3D is ubiquious in the Building profession – BIM

Autodesk REVIT


3D is ubiquious – BIM

• State >2,5 mio Euro => BIM

• Municipalities >0,7 mio Euro => BIM

• Competition phase demands 3D model (IFC)

• Digital exchange of information via project web

• Quantity take-off from IFC model

• Digital handover of facility management information regutaed through

Information and Communication Technologycontracts (ICT-contracts)

DENMARK

SINCE 2007: BIM DEMANDED FOR PUBLIC BUILDINGS


UNITED KINGDOM

FROM 2016:

3D is ubiquious – BIM

“…The UK Government has mandated that all

public projects in the UK will be delivered using

BIM by 2016. This is driving the private sector

to adopt Building Information Modelling

processes, which is now becoming a common

requirement for all major projects….”


Stakeholder – Interviews, Workshops, Datasets

Cultural Heritage Institutions

Land Surveyors

Architects

Krydsrum Arkitekter (DK)

Zeso Architects (DK)

BIPS (DK)

KRH (DK)

DTU (DK)

LE34 (DK)

Plan3D (DE)

COWI (DK)

HCU Hamburg (DE)

ATS (SE)

FARO (DE)

Bygningsstyrelsen (DK)

Copenhagen Properties (DK)

Danish Techincal University (DK)

Bane Danmark (DK)

Lufthavn København (DK)

NTNI (DK)

DSV (DK)

Falun Kommun (SE)

Building Owners

Fortifikationsverket (The Swedish Fortifications Agency) (SE)

Statens fastighetsverk (The National Property Board of Sweden)

Statsbygg (NO)

Direktoratet for byggkvalitet in Norway (NO)

Contractors in the Netherlands (NL)

Rijksgebouwendienst (NL)

Dalux (DaluxFM)

NTI (Mdoc /MdocFM)

Catenda (NO)

dRofus

NExtFM (NL)

Mainmanager (Is)

Think project (DE)

Nationaal Archief (National Archive of the Netherlands)

Statsbiblioteket - State and University Library, Aarhus

(DK)

Flemish Architecture Archive (NL)

Riksarkivet (The National Archives) (SE)

Riksantikvaren Norway (NO)

Arkivverket (NO)

Aarhus City Archive (DK)


Life-cycle of BIM models

Integrated Simulation

Cultural Heritage

Institutions

Engineers Construction Companies

Architects

Land Surveyors

Building Owners


Project Web

Architect

BIM model

Construction Engineer

BIM model

MEP Engineer

BIM model

Owner/developer

Building Practice with BIM in Denmark

Lund Cristallen by DURAARK partner CCO architects


Building Owner: Facility Management

Building Data in the Operational Phase of a

building is a “live object”

• new building related data is constantly generated

(and old data overwritten)

• Stakeholders consider a FM system as archive

• Stakeholders see a challenge to keep building data up

to date

Source Dalux FM


Life-cycle of BIM models



Life-cycle of BIM models in relation to lifetime



Change of data during operational phase of buildingd



Evolution of building data



Future Re-use of Building Data



Building and Building Data Lifecycle

• How to find the right

information?

• How to trust the

information?

• How to use the

information?


www.DURAARK.eu


DURAARK Consortium

DURAARK (Durable Architectural Knowledge)

is a collaborative project developing methods

and tools for the semantic enrichment and

long-term preservation of architectural

knowledge and data. It is funded through the

European Commission’s FP7 Programme and

is running between 02/2013 — 01/2016.

www.duraark.eu


Architectural Data in DURAARK

BIM/IFC Scan/E57 Image


BIM

SCAN

IFD

bSI

image

ccs

dbk

bips

ifc

Connecting and Compare

BIM Scan Foto


Motivation: Enrich Architectural data, preserve meaning

Dataset provided by Plan3D / Berlin

2D Data Geo Data Point Cloud Data BIM Linked Data Cloud


Integration of Data into Design & Retrofitting Workflow

Geo Data

Neue Heilanstalten Berlin / Architekt: Ludwig Hoffmann 1900-1914

Linked Data Cloud


DURAARK Longterm Archiving system

Preservation SystemLong time archive

SIP Container

Search & Retrieve

As-built Point Cloudscanner | point software

DURAARK WorkbenchUI + Service Platform

DURAARK

Metadataextraction and

enrichment

Semantic Digital Observatory

crawl, link, align

As-planned BIMBIM software

Enriched BIM with Point Cloud

BIM software

BIM from Point Clouds

Difference Detection

as-built <-> as-planned

ComparisonPoint Clouds and

BIM in time

Δt1,t2

Semantic Digital Archive

Organize, archive, expose

http://workbench.duraark.eu

Restful Interface, Docker


Objects - Properties – Machine Search in 3d Model

Autodesk REVIT


© Horrocks, Oxford University

Search: Semantic Web technology

Now... that should clear up a few things around here


Linking Data – World Wide Web - Linked Open Data Cloud


Meta Data Extraction

Semantic Digital Archive (SDA)

consists of three components:

1. Meta Data Extraction and Semantic

Enrichment

• Industry Foundation Classes (IFC),

STEP Physical File Format (SPFF)

• created with native BIM Software

(e.g. ArchiCAD, Nemetschek, Revit)

As-planned BIMBIM software

Metadataextraction and enrichment


BIM

GIS

SDO: Crawling relevant data sets for enrichment

Semantic Digital Observatorycrawl, link, align


Existing models and vocabularies

Connecte

dness

Specific to the Built Environment


http://www.okstra.de/


SDO: Clustering datasets





Enrichment

- Extract meta data from E57 and IFC files

submitted to the archive.

- Enrich by curator and automated methods

2. Semantic Digital Observatory (SDO)

- Discover relevant data sets for semantic

enrichment

- Cluster similar data based on initial seed list


Search in Building Data - Exposed archived meta data




Enrichment

- Extract meta data from E57 and IFC files

submitted to the archive.

- Enrich by curator and automated methods

2. Semantic Digital Observatory (SDO)

- Discover relevant data sets for semantic

enrichment

- Cluster similar data based on initial seed list

- Allow manual validation of discovered links

through croudsourceing

3. Semantic Digital Archive Storage

(SDAS)

- Store meta data of archived content and

expose as Linked Data

Metadataextraction and enrichment


Semantic Digital Archiveorganize, archive, expose

http://mimas.cgv.tugraz.at/search


Semantically Poor and Rich Data

Carlsberg Brewery/CopenhagenSource LE34


3D is ubiquious – Faster and Automated

ScanBot by FaroLabs

Zebedee by CSIRO

ScanCoptor by FaroLabs

Project tango by google


Why Automatic Detection Of Semantic Information?

Hullo and Thibault, 2014

Global Time allocation for creation of Architectural Data from 3D Laserscans

Laser acquisition

Laser processing

RGB Acquisition

RGB processing

CAD reconstruction


Automatic Reconstruction - Point Cloud to BIM

39 05 / 28 / 15 Martin Tamke (CITA) / Copenhagen • Morten Myrup (CITA) Copenhagen

Semantically enriched Point Cloud

Surplus – Properties of Spaces / Room Connectivity

recognition.mp4


Definition of Spaces (use in Facility Management)

• Morten Myrup (CITA) Copenhagen

Autodesk Revit Solibri Model Checker

recognition.mp4


Neighbor

Definition of Connections: Search in Graph

0

1 2 3

6 5 4

Building 0

Connection


The future of BIM is semantic

Implementation of Semantic

capabilities into the iFC Schema (BIM)

• buildingSMART linked data working

Group (Jacob Beetz TUE)

Integration of Point Cloud data in the

IFC schema

• Submitted to buildingSMART for

standardization




information?

• How to create trust into

the information?

• How to use the

information?


Point Cloud Analysis (Deviation & Difference)

http://www.gexcel.it http://www.gexcel.it

LE34 – Trimple RealWorks http://www.gexcel.it

Deviation from Plane

http://www.gexcel.it/




Semanticaly aware Difference Detection

Point Cloud Data BIM

?


DURAARK Prototype – Semantic Difference Detection

source: Statsbyg Risløkka




information?

• How to create trust into

the information?

• How to use the

information?


Prototype Evaluation in Architectural Workflows

Import

E57

IFC

Allocation

Registration

Transfomation

Subsample

Query &

Select

IFC

Reconstruction

2D Cropping

3D Cropping

Clustering

Analysis

Difference

Detection

Planar Deviation

Output

Visualisation

Export

Data Data for

Planning

Dataset: Nøreport Station Copenhagen / Grontmij

Components from DURAARK Workbench Longterm Archive


Evaluation of DURAARK prototype

Current manual Approach Measured during Nygade Use Case with Zeso Architects

12h Manual Measurements

4h Registration of materials and object classification

25h BIM Modelling

41h Total

WP7 Duraark Prototype workflow

9h LaserScanning

12h Point cloud post-processing & registration

1h Reconstruction of BIM model 4h Manual Adjustment of model to drawing conventions

4h Registration of materials and object classifications

0,1h Quality Control with Difference-Analysis

30h Total

Point Cloud Data

BIM

Use Case Nygade / Copenhagen with Zeso Architects – 107 Scans


Find more data Detecting Information through combination of

Approaches


DURAARK component: Reconstruction of Geometry


Projection


Projection & Orthophotogeneration


Detection of electrical appliances


Supervised Learning on generated Orthophotos


Referencing of detection in 3d Model


[email protected]

www.duraark.eu http://workbench.duraark.eu

https://github.com/DURAARK


Comparing As Built – Difference Detection

Point Cloud Data BIM


Find Deviations – Geometrical or over Time

Point Cloud Data Point Cloud Data


Automatised Detection of Architectural Meaning


Find Deviations – Geometrical or over Time

Point Cloud Data Point Cloud Data


Prototype Evaluation with Stakeholders

Plan 3D / Haus 30 / Berlin KADK / Diakonissenstiftelsen / Copenhagen LE 34 /Højbro Plads / Copenhagen

Zeso Architects / Nygåde / Copenhagen

LE 34 / Facade / Copenhagen

Hotel Nyborg Strand / Nyborg Strand

Statsbyg / Rikslokka / Oslo


CITA Research Method – Demonstrators


3D Registration – Laser Scanning

scan by


3D Registration – Automated feature detection

DURAARK ENRICHING BIM AND POINT CLOUD DATA FOR THE … Tamke.pdf · 1 05 / 28 / 15 Martin Tamke...

Documents

Transcript of DURAARK ENRICHING BIM AND POINT CLOUD DATA FOR THE … Tamke.pdf · 1 05 / 28 / 15 Martin Tamke...